Error on sysreg.SUR

[Andres R]

Hello,

I am not sure this is the right forum to ask such questions - I am encountering the below error that appears after running this bit of code. Is there a solution to this problem? I am running Python 3.6 and stats models 0.8.0.

Thanks,

Andres

from statsmodels.compat.python import lmap, asbytes

import numpy as np

import statsmodels.api as sm

from statsmodels.sandbox.sysreg import *

#for Python 3 compatibility

# Seemingly Unrelated Regressions (SUR) Model

# This example uses the subset of the Grunfeld data in Greene's Econometric

# Analysis Chapter 14 (5th Edition)

grun_data = sm.datasets.grunfeld.load()

firms = ['General Motors', 'Chrysler', 'General Electric', 'Westinghouse',

        'US Steel']

#for Python 3 compatibility

firms = lmap(asbytes, firms)

grun_exog = grun_data.exog

grun_endog = grun_data.endog

# Right now takes SUR takes a list of arrays

# The array alternates between the LHS of an equation and RHS side of an

# equation

# This is very likely to change

grun_sys = []

for i in firms:

    index = grun_exog['firm'] == i

    grun_sys.append(grun_endog[index])

    exog = grun_exog[index][['value','capital']].view(float).reshape(-1,2)

    exog = sm.add_constant(exog, prepend=True)

    grun_sys.append(exog)

# Note that the results in Greene (5th edition) uses a slightly different

# version of the Grunfeld data. To reproduce Table 14.1 the following changes

# are necessary.

# grun_sys[-2][5] = 261.6

# grun_sys[-2][-3] = 645.2

# grun_sys[-1][11,2] = 232.6

grun_mod = SUR(grun_sys)

grun_res = grun_mod.fit()

print("Results for the 2-step GLS")

print("Compare to Greene Table 14.1, 5th edition")

print(grun_res.params)

Error message:

/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/numpy/core/records.py:507: FutureWarning: Numpy has detected that you may be viewing or writing to an array returned by selecting multiple fields in a structured array. 

This code may break in numpy 1.13 because this will return a view instead of a copy -- see release notes for details.

  return obj.view(dtype=(self.dtype.type, obj.dtype))

/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/statsmodels/tsa/tsatools.py:121: FutureWarning: Assignment between structured arrays with different field names will change in numpy 1.13.

Previously fields in the dst would be set to the value of the identically-named field in the src. In numpy 1.13 fields will instead be assigned 'by position': The Nth field of the dst will be set to the Nth field of the src array.

See the release notes for details

  x = x.astype(np.dtype(descr))

/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/numpy/linalg/linalg.py:1587: FutureWarning: elementwise == comparison failed and returning scalar instead; this will raise an error or perform elementwise comparison in the future.

  return int(not all(M==0))

Traceback (most recent call last):

  File "delete.py", line 68, in <module>

    grun_mod = SUR(grun_sys)

  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/statsmodels/sandbox/sysreg.py", line 129, in __init__

    self._cols[i]:self._cols[i+1]] = sys[1::2][i]

  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/scipy/sparse/lil.py", line 363, in __setitem__

    i, j = self._index_to_arrays(i, j)

  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/scipy/sparse/sputils.py", line 356, in _index_to_arrays

    i = self._slicetoarange(i, self.shape[0])[:, None]

  File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/scipy/sparse/sputils.py", line 262, in _slicetoarange

    start, stop, step = j.indices(shape)

TypeError: slice indices must be integers or None or have an __index__ method